Explaining the Role of Policy Factors on Institutional Building of Risk Management in Rural and Agricultural Regions of “Rostov on Don” in Russian Federation

Subject Areas : Agricultural Extension and Education Research

Shahab Alddin Shokri ¹ ( Assistant professor of Agricultural Economics, Faculty of Agriculture and Basic Sciences, Roudehen Branch, Islamic Azad University, Roudehen, Tehran, Iran. )
Alexey Urich Arkhipov ² ( Professor & Head of the Higher School of Business, Southern Federal University, Rostov on Don, Russian Federation )
Ulia Viacheslavovna Filonenko ³ ( Associate Professor of Economic Theory Department, Faculty of Economics, Southern Federal University, Rostov on Don, Russian Federation )
Belokrilova Olga Spiridonova ⁴ ( Professor of Economics Faculty, Southern Federal University, Rostov on Don, Russian Federation. )
Marina Sanikova ⁵ ( Associate Professor & Candidate of Economical Sciences (Ph.D.). Saratov State Agrarian University, Department of Economic & Management, Rostov on Don, Russian Federation. )

Received: 2019-06-09 Accepted : 2019-06-09 Published : 2019-05-22

Keywords: Institutional building, policy making, Structural model, Rostov on Don, Russian Federation,

Abstract :

The purpose of this research was to specify a structural model in order to estimate the impact of policymaking factors (financial policy and energy policy) on institutional components related to the risk management in agricultural and rural areas of Rostov on Don. At the first stage, we explored and ranked a risk profile in agriculture based on the Rostov situation including climate, production, socio-economic, agricultural market, labor market and land regulation. At the next stage, the main strategies were identified in order to manage related risks and increase economic resilience. The data used in this paper were collected through a structured questionnaire from 75 subject matter specialists in the field of economics and agricultural economics from Southern Federal University (Rostov on Don) and Saratov State Agrarian University along with a number of governmental experts. Two confirmatory models of policy making and institutions fitted the data or supported by the obtained sample data. Resulted from the structural model showed that two factors of “financial policy” and “energy policy” explains 48 and 38 percent of variance in “institutional technology” and “institutional building” respectively. 

References:

Analytical Center of Agribusiness in Russia. (2017). Agricultural regions in Russia. Retrieved from http://ab-centre.ru/page/selskoe-hozyaystvo-regionov-rossii (in Russian).

Antwi E.K., Boakye-Danquah J., Owusu A.B., Loh S.K., Mensah R., Boafo Y.A., & Apronti, P.T. (2015) Community Vulnerability Assessment Index for Flood Prone Savannah Agro-ecological Zone: A Case Study of Wa West District, Ghana. Weather and Climate Extremes, 10: 56–69. Retrieved from: https://doi.org/10.1016/j.wace.2015.10.008 .

Belokrilova O. C., & Cherkezov, N. V. (2014). Regional policy of support diversification in agriculture in terms of WTO regulations. Southern Federal University, Rostov on Don, Russia, 184 p (in Russian).

Brown, T.A. (2006). Confirmatory factor analysis for applied research. New York: The Guilford press.

Costantini, V., & Liberati, P. (2014). Technology transfer, institutions and development. Technological Forecasting and Social Change, 88, 26-48. Retrieved from:http://dx.doi.org/10.1016/j.techfore.2014.06.014.

Derbali, A., & Hallara, S. (2016). Systemic risk of European financial institutions: estimation and ranking by the marginal expected shortfall. Research in International Business and Finance, 37: 113-134. Retrieved from: http://dx.Doi.org/10.1016/j.ribaf.2015.10.013.   

Economic Commission for Latin America and the Caribbean and Inter-American Development Bank. (2000). A matter of development: how to reduce vulnerability in the face of natural disasters. Retrieved from: http://preventionweb.net/go/5461.

Endfield, G. H. (2011). The resilience and adaptive capacity of social-environmental systems in colonial Mexico. PANS, 109 (10): 3676-3681. Retrieved from: https://doi.org/10.1073/pnas.1114831109.

Fałkowski, J., Olper, A. (2013). Political competition and policy choices: the evidence from agricultural protection. Agric. Econ. 45 (2): 143-158. Retrieved from: http://onlinelibrary.wiley.com/doi/10.1111/agec.12018/abstract .

FAO. (2016). The Russian Federation and FAO, Partnering for global food and nutrition security. Retrieved from: http://www.fao.org/3/a-au083e.pdf .

Granberg, L. (2015) Structural Change in the Finnish and Russian Countryside’s: a Comparative Analysis of Two Different Types of Society. Mir Rossii, 24 (3): 160–175. Retrieved from: https://mirros.hse.ru/article/view/493  (in Russian).

Girard, M. (2015). Trade and Transition: Russia's Agricultural Pitfalls and Prospects for the 21st Century. University of Maine, Honors College. Paper 213. Retrieved form http://digitalcommons.library.umaine.edu/honors/213

Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate data analysis. (7nd ed.). USA: Pearson Prentice Hall.

Higgins, A., McFallan, S., Laredo, L., Prestwidge, D., & Stone, P. (2015). TRANSIT – A model for simulating infrastructure and policy interventions in agriculture logistics: Application to the northern Australia beef industry. Computers and Electronics in Agriculture, 114: 32-42. Retrieved from: http://dx.doi.org/doi:10.1016/j.compag.2015.03.018 .

Kalugina, Z. I. (2014). Agricultural Policy in Russia: Global Challenges and the Viability of Rural Communities. International Journal of Sociology of Agriculture and Food, 21 (1): 115-131. Retrieved from: http://ijsaf.org/archive/21/1/kalugina.pdf Kreidenko, T. F., & Mironova, M. N. (2012). Modern small business in Russia. Regional Research of Russia, 2 (4), 347-352. Retrieved from: https://doi.org/10.1134/S2079970512040065 .

Lerman, Z., & Shagaida, N. (2007). Land policies and agricultural land markets in Russia. Land Use Policy, 24: 14-23. Retrieved from: https://www.researchgate.net/publication/222691750 .

Liefert, W. M. (2009). Decomposing changes in agricultural price gaps: an application to Russia. Agric. Econ. 40 (1): 15-28. Retrieved from: http://onlinelibrary.wiley.com/doi/10.1111/j.15740862.2008.00341.x/abstract .

Liefert, W. M., & Liefert, O. (2012). Russian Agriculture during Transition: Performance, Global Impact, and Outlook. Applied Economic Perspectives and Policy, 34, (1): 37–75. Retrieved from: https://doi.org/10.1093/aepp/ppr046 .

Lunze, K., Yurasova, E., Idrisov, B., Gnatienko, N., & Migliorini, L. (2015) Food Security and Nutrition in the Russian Federation – a Health Policy Analysis. Global Health Action. Retrieved from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481043 .

Martin, R., & Galang, N. (2014). Divergent diffusion: Understanding the interaction between institutions, firms, networks and knowledge in the international adoption of technology. Journal of World Business, 49 (4): 512-521. Retrieved from: http://dx.doi.org/10.1016/j.jwb.2013.12.005.

OECD (Organization for Economic Co-operation and Development). (2014). OECD economic surveys, Russian federation. OECD Publishing, Retrieved from: http://www.oecd.org/eco/surveys/Overview_RUSIA_2013.pdf .

Rada, N., Liefert, W., & Liefert, O. (2017). Productivity Growth and the Revival of Russian Agriculture, A report summary from the Economic Research Service. United States Development of Agriculture. Economic Research Service. Retrieved from: https://www.ers.usda.gov/webdocs/publications/83285/err-228.pdf?v=42844 .

Rutten, L. (2012). Innovative agricultural finance and risk management Strengthening food production and trade in the transition region. FAO Investment Center. Working Paper, (7), FAO publishing. Retrieved from: http://www.fao.org/3/a-at658e.pdf .

Shagaida, N., Karlova, N., Uzun, V., & Yanbykh, R. (2014). Russian Agriculture: the impact of sanctions. Retrieved from: https://ssrn.com/abstract=2658006 .

Shokri, Sh. A., Arkhipov, A., Belokrylova. O., & Filonenko, Y. (2017). Vulnerability Assessment of the Agricultural Economy in Russia (Using the Example of Rostov Region, Southern Federal District). Universe of Russia. (2): 82-102. Retrieved from: https://mirros.hse.ru/article/view/4867/5230 .

Swinnen, J. F. M., Banerjee, A. N., & Gorter, H. de. (2001). Economic development, institutional change, and the political economy of agricultural protection, an econometric study of Belgium since the 19th century. Agric. Econ. 26 (1): 25-43. Retrieved from: http://onlinelibrary.wiley.com/doi/10.1111/j.1574-0862.2001.tb00052.x/abstract .

Tabachnick, B.G., & Fidell, L.S. (2013). Using multivariate statistics. (6nd ed.). USA: Pearson Education.

Westen, D., Rosenthal, R. (2003). Quantifying construct validity: Two simple measures. Journal of Personality and Social Psychology, 84 (3): 608-618. Retrieved from: https://dash.harvard.edu/bitstream/handle/1/3708469/rosenthal_quantifyingconstruct.pdf?sequence= 1.

World Bank Data Sheet. (2017). Retrieved from: www.worldbank.org .

Zagorchev, A., & Gao, L. (2015). Corporate governance and performance of financial institutions. Journal of Economics and Business, 82 (C): 17-41. Retrieved from: https://doi.org/10.1016/j.jeconbus.2015.04.004.

Zhebit, M. (2013). Investing in Russian agriculture: where there is a will there is a way. Russian Survey. Retrieved from: http://www.russian-survey.com/market-breakdown/203-investing-in-russian-agriculture-where-theres-a-will-theres-a-way .